Quantifying Genetic Innovation: Mathematical Foundations for the Topological Study of Reticulate Evolution
Michael Lesnick, Ra\'ul Rabad\'an, Daniel I. S. Rosenbloom

TL;DR
This paper develops a mathematical framework using persistent homology to quantify genetic recombination, introducing the novelty profile as a stable statistic to estimate recombination events from topological data.
Contribution
It introduces the novelty profile and establishes methods to bound it using barcodes in low-recombination regimes, advancing topological analysis of evolutionary histories.
Findings
The 1st barcode provides a lower bound on recombination events.
In low-recombination regimes, higher barcodes are typically empty.
Simulations show the sensitivity of barcode intervals to recombination.
Abstract
A topological approach to the study of genetic recombination, based on persistent homology, was introduced by Chan, Carlsson, and Rabad\'an in 2013. This associates a sequence of signatures called barcodes to genomic data sampled from an evolutionary history. In this paper, we develop theoretical foundations for this approach. First, we present a novel formulation of the underlying inference problem. Specifically, we introduce and study the novelty profile, a simple, stable statistic of an evolutionary history which not only counts recombination events but also quantifies how recombination creates genetic diversity. We propose that the (hitherto implicit) goal of the topological approach to recombination is the estimation of novelty profiles. We then study the problem of obtaining a lower bound on the novelty profile using barcodes. We focus on a low-recombination regime, where the…
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